Most Frequently Tagged Accounts within the Dataset

There were five main categories that popped up in tagged accounts: Company, Health Organization, Individuals, News Organizations/Personalities, Politicians

Politicians and News Agencies were the most mentioned with Trump and various world leaders being mentioned the most.

Most used hashtags within the Dataset

Most of the hash tags within the Data Set had something to do with COVID-19, likely due to that being how the data was collected for the data set

Interactive World Map: Highlights the countries we have data on, the darker the shade the more tweets we have for that country

The darker the country the more tweets within the data set were from that country. The country with the most tweets was the United States, our main point of interest.

Tweet Locations: Shows the cities that have tweets tagged within them and the number of tweets

This shows the number of tweets from a city, giving us a general idea of where these tweets are being published in the United States.

This shows that major population centers generally have more data.

Sentiment by State: lighter colors represent more negative sentiment

The darker the state the more positive the sentiment towards COVID-19. This is not a perfect representation due to some states only having a few tweets being collected on this particular day.

The more tweets that were collected caused the sentiment to be less extreme.

Sentiment Density Plots split by Individual and State

This shows the difference in how extreme the sentiment is betweet state tweets being averaged and individual tweets. Some tweets showed extremely positive sentiment while others were extremely negative.